5 papers
Who Gets Credit or Blame? Attributing Accountability in Modern AI Systems
Shichang Zhang, Hongzhe Du, Jiaqi W. Ma +1
Modern AI systems are typically developed through multiple stages-pretraining, fine-tuning rounds, and subsequent adaptation or alignment, where each stage builds on the previous o…
How Faithful Is Trajectory-Based Data Attribution? Error Sources, Remedies, and Practical Guidelines
Junwei Deng, Pingbang Hu, Suliang Jin +4
Trajectory-based data attribution methods estimate the influence of training samples on model predictions by unrolling the training trajectory. They are widely used in applications…
Computational Copyright: Towards A Royalty Model for Music Generative AI
Junwei Deng, Xirui Jiang, Shiyuan Zhang +5
The rapid rise of generative AI has intensified copyright and economic tensions in creative industries, particularly in music. Current approaches addressing this challenge often fo…
Generalized Group Data Attribution
Dan Ley, Suraj Srinivas, Shichang Zhang +2
Data Attribution (DA) methods quantify the influence of individual training data points on model outputs and have broad applications such as explainability, data selection, and noi…
Efficient Ensembles Improve Training Data Attribution
Junwei Deng, Ting-Wei Li, Shichang Zhang +1
Training data attribution (TDA) methods aim to quantify the influence of individual training data points on the model predictions, with broad applications in data-centric AI, such…